Evaluating the effectiveness of urban hedges as air pollution barriers: Importance of sampling method, species characteristics and site location

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Abstract

Urban hedgerows can act as barriers to roadside particulate air pollution, but details on methodologies to quantify pollutant capture, most efficient species to use, and practical planning advice are still evolving. We aimed to compare three widely used approaches to quantify particulate accumulation and deposition, and to ascertain the most cost-effective and robust approach for the rapid screening of various types of hedges. Secondly, using the most efficient methodology, we screened the summertime deposition of particulates on roadside hedges in Reading (UK), not just on species with differing leaf surface characteristics, but also along a transect of the hedge depth. Finally, we also compared particles’ capture by hedge leaf surfaces in locations with different traffic intensities, to try and ascertain the extent of reduction of particles’ concentration in various hedge types and urban locations. Results suggest that the gravimetric determination of particulate capture was most rapid and cost-effective, while being least technically demanding. We confirmed that hairy and more complex leaves captured most particulates, particularly in the >10 μm range. However, species choice only had a significant impact on the extent of capture on major roads, where the pollutant concentrations were highest. Furthermore, only hedge depths in excess of 2 m were found to noticeably reduce the concentration of fine particles in species with less capacity for particulates’ capture. Findings complement the growing body of knowledge to guide urban and landscape planners in choosing the most appropriate species to mitigate air quality in various urban contexts.

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Blanuša, T., Qadir, Z. J., Kaur, A., Hadley, J., & Gush, M. B. (2020). Evaluating the effectiveness of urban hedges as air pollution barriers: Importance of sampling method, species characteristics and site location. Environments - MDPI, 7(10), 1–21. https://doi.org/10.3390/environments7100081

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